CC BY
109
MARKAL Application for Analysis of Energy Efficiency in Economic Activities of the Republic of Moldova and Feasible use of Renewable Energy
Sources
Sergiu Robu, [email protected], Elena Bikova, [email protected] Institute of Power Engineering of Academy of Sciences of Moldova,
Philip Siakkis, fsiakkis@,cres.gr CRES - Centre for Renewable Energy Sources, Greece Dr. George Giannakidis, [email protected] CRES - Centre for Renewable Energy Sources, Greece Abstract. The paper presents results of analyses of energy efficiency measures and renewable energy sources implementation in the Republic of Moldova using MARKAL model. Detailed analyses of four scenarios are presented for: Reference Scenario; Energy Efficiency Scenario; Renewable Energy Sources Scenario; Energy Efficiency&Renewable Energy Scenario. Energy savings and costs are identified for implementation of renewable energy sources and Energy efficiency measures.
Key words: energy efficiency, renewable energy sources, scenarios assessment.
UTILIZAREA PROGRAMULUI MARKAL PENTRU ANALIZA EFICIENJEI ENERGETICE IN ECONOMIA NAJIONALA A REPUBLICII MOLDOVA §I IMPLEMENTAREA SURSELOR
RENOVABILE DE ENERGIE Sergiu Robu, [email protected], Elena Bikova [email protected] Institutul de Energetica al Academiei de §tiinte a Moldovei,
Philip Siakkis, fsiakkis@cres. яг CRES - Centrul Pentru Surse Renovabile de Energie, Grecia Dr. George Giannakidis, ssian@cres. sr CRES - Centrul Pentru Surse Renovabile de Energie, Grecia Rezumat. Articolul prezinta rezultatele cercetarii privind implementarea masurilor de eficienta energetica §i a surselor renovabile de energie in Republica Moldova, cu ajutorul modelului MARKAL. Sunt prezentate rezultatele analizei a patru scenarii: Scenariul de referinta, Eficienta Energetica, Surse renovabile de energie, Eficienta Energetica §i Surse renovabile de energie. Sunt identificate costurile §i economiile de energie in urma implementarii surselor renovabile de energie §i a masurilor de eficienta energetica.
Cuvinte-cheie: eficienta energetica, surse renovabile de energie, evaluarea scenariilor
ПРИМЕНЕНИЕ ПРОГРАММЫ MARKAL ДЛЯ АНАЛИЗА ЭНЕРГОЭФФЕКТИВНОСТИ В НАЦИОНАЛЬНОЙ ЭКОНОМИКЕ РЕСПУБЛИКИ МОЛДОВА С УЧЕТОМ РАЦИОНАЛЬНОГО ИСПОЛЬЗОВАНИЯ ВОЗОБНОВЛЯЕМЫХ ИСТОЧНИКОВ ЭНЕРГИИ
Серджиу Робу, [email protected], Е.В. Быкова, [email protected] Институт Энергетики Академии Наук Молдовы,
Филип Сиаккис, fsiakkis@cres. яг CRES - Центр Возобновляемых Источников Энергии, Греция Др. Георге Гианнакидис, ssian@cres. sr CRES - Центр Возобновляемых Источников Энергии, Греция Аннотация. Статья представляет результаты анализа внедрения мер по энергосбережению и использования возобновляемых источников энергии в Республике Молдова, с помощью модели МАРКАЛ. Представлен детальный анализ четырех сценариев: базового сценария, внедрения мер по энергоэффективности, внедрения возобновляемых источников энергии, энергоэффективности и возобновляемых источников энергии. Определен потенциал экономии энергии, и стоимости внедрения мер по энергосбережению и освоению возобновляемых источников энергии.
Ключевые слова: энергоэффективность, возобновляемые источники энергии, анализ сценариев.
1. Introduction
MARKAL is a linear programming model that minimizes total energy system cost. A distinction must be made between cost and price, which are related, respectively, to production and consumption of products (i.e., resources, energy carriers, and energy services) as they flow through the Reference Energy System[1]. In MARKAL, payment by a producer to supply a demand for a product is “cost.” Payment by a distributor or consumer to purchase a product is “price.”
The US Agency for International Development sponsored the Regional Energy Demand Planning (REDP) initiative which aimed at providing a robust framework to enable the countries of Southeast Europe, including the Republic of Moldova, to examine aspects of the future demand for energy in the region. Owing to its widespread use throughout the world [some applications: 7-14] the MARKAL energy system model was used as the organizing platform and primary analysis tool for REDP. This tool is expanded in the USAID/HELLENIC AID cooperative energy program SYNENERGY and it will also be used in the Observer Countries of the Energy Community, like the Republic of Moldova.
The Republic of Moldova is an Eastern European state, located in the South-East of the continent; its neighbors are: Romania in the West, Ukraine in the East. Total area of the country is 33845 thou km2 with mainly a hilly plain. Moldova has a population 3.589 milion inhabitants and a GDP of 7000 mil Euro PPP2006.
The Republic of Moldova has very limited fossil fuel resources (~ 2% of the total consumption), around 98% of primary energy is imported. Crude oil is not imported directly to Moldova. The size of the country's liquid fuel market is too small to allow domestic refining capacity to operate competitively. Oil products are imported from the Ukraine, Romania and Russia (8.46 PJ of gasoline, 13.86 PJ of light oil products and 0.68 PJ of heavy oil products in 2006). Natural gas imports used to be available from Russia at a FOB price of 3.375 €2006/GJ [2]. In 2009 the gas import price has increased to 7.4 €2006/GJ or 250 $2006/1000 m3 (heating value is 33.74 MJ/m ). In 2006, about 48 PJ of natural gas were imported exclusively from Russia. Due to the geographical location of Moldova with respect to the international natural gas transmission system, no alternatives to the gas imports from Russia are included in the present energy model. In 2006, 3.48 PJ (134 thousand tones) of coal and coke were imported from the Ukraine and Russia [5]. Additional coal imports are considered in analyses due to construction of coal-fired power plant since 2015.
It is important to note that only about one quarter of total electricity consumption relies on national energy generation sources. The relative high degree of dependence from foreign sources compared to other states has to be taken into account when selecting the most representative fuel cycles for the whole sector. Taking this into account it is reasonable to say that the following years will see a further development of thermoelectric capacity - mainly combined cycle (natural gas fired) - as opposed to coal-fired power plant and renewable. As for the hydropower, we will refer to Hydro Power Plant - Costeshti, a small producer of 16MWinst., located in northern Moldova. None hydro resources for new projects are available.
2. Overview of Analyses Undertaken
The following scenarios are considered for analyses:
> Reference Scenario (Business as Usual Scenario) with slower replacement of existing end use demand devices, energy prices according to WEO 2009.
> Renewable Energy Target Scenario (using IPA-derived target) -10% biofuels in 2020 for transport sector
> Energy Efficiency Scenario (with greater penetration of efficient end-use technologies)
> Renewable Energy Target plus Energy Efficiency Scenario combines RE&EE scenarios
Reference Scenario represents Business as Usual development of energy system of Moldova without major changes in structure and with slower replacement of existing end-use demand devices, comparing to other scenario. The forecast of energy prices is according to WEO 2009 Report [3]. Population of the Republic of Moldova is 3589 mil inhabitants in base year (2006) and has a growth rate of 0.33% per year [6], or 3842 mil in 2030. GDP has a value of 7000 mil Euro,PPP2006 in year 2006 and has a growth rate of 6% per year, by the end of study period the value of GDP is estimated to be around 28000 mil Euro, PPP2006 [4]. The main industrial activity of Moldova in 2006 is Food industry with 1136 mil. Euro or 69% of Industrial sector; followed by Other activities of 201 mil. Euro, or 12%; and Iron-Steel 128 mil. Euro, or 8%.
The main fuel is natural gas with 47.75 PJ of total 72 PJ primary energy supply in 2006; followed by Electricity of 10.3PJ. Biomass supply is 3.24 PJ in 2006 and will double to 6.3 PJ in 2030. Coal supply is increasing due to coal-fired power plant which in planned to be operated starting with 2015. The Figure 2.1 represents the Primary Energy Supply in Reference Scenario, without Transport Sector:
Oil
Nuclear
Natural
Gas
■ LPG
■ Electricity
■ Coal
■ Biomass
Fig. 2.1 Primary Energy Supply [PJ]
Residential sector remain the main consumer of final energy with 29.5PJ in 2006, increasing to 44.4 PJ in 2030. Industrial sector’s final energy consumption is second largest with 13PJ in 2006, increasing to 18.7PJ in 2030. Commercial sector’s final energy consumption has the highest growth rate from 10PJ in 2006 to 19PJ in 2030. Final Energy Consumption by Sector is represented in Figure 2.2.
Fig. 2.2. Final Energy Consumption by Sector [PJ]
Natural gas will remain the main fuel for final energy consumption during the study period, with 21PJ in 2006 increasing up to 27PJ in 2030. Electricity has the highest growth rate from 10PJ in 2006 to 25PJ in 2030. Share of heat demand will increase from 12PJ in 2006 to 16 PJ in 2030. The Figure 2.3 below represents the Final Energy Consumption by Fuel.
Fig. 2.3. Final Energy Consumption by Fuel [PJ]
Consumption of Natural Gas and Electricity remains the main source of energy for Commercial, Industrial and Residential sector. Residential sector consumes mainly natural gas with 12.7PJ in 2006 to 14.4PJ in 2030, followed by electricity of 4.1PJ in 2006 and 14.6PJ in 2030. Heat
consumption by Residential sector remains almost at the same level of 5.7PJ during the study period. Coal consumption increases from 2.4PJ in 2006 to 3.8PJj in 2030. Figure 2.4 shows the Residential Fuel Consumption during the study period.
cn _ □ Residential Renewables (other) □ Residential Oil
-
- __ — □ Residential Natural Gas
^ - I—I
__ — □ Residential Low-
OU 25 -20 - I—I — — temperature Heat
-> — _ — □ Residential LPG
Q_ _ — — —
10 - c _ — □ Residential Electricity
_ — — — — — □ Residential Coal
— — — — —
O CD CM o O0> O CM O LO O CO Ot- OTf or-- oo CM O CM T- CM T- CM T- CM CM CM CM CM CM CM CO □ Residential Biomass
Fig. 2.4. Residential Fuel Consumption
Residential fuel and energy consumption is mainly for space heating - 60% or 17.5PJ in 2006 and 23PJ in 2030; followed by cooking - 20% or 6PJ in 2006 increasing to 7PJ in 2030; and water heating - 12% or 3.6PJ in 2006 increasing to 7PJ in 2030. Residential Cooling is increasing to 2.4PJ in 2030 from 0.08PJ in 2006. From 0.6PJ in 2006 to 1.4PJ in 2030 is increasing residential lighting.
In year 2006 Moldova has imported 10.4PJ of electricity or 70% of total demand. Import of electricity is decreasing till 2030 to 26% of total or to 7.6PJ. Production of electricity by existing gas-fired power plants is increasing from 3.9PJ in 2006 to 5PJ in 2012, followed by a decreasing to 3PJ in 2030, due to replacement of existing gas-fired power plants by a new coal-fired power plant starting with 2015. Hydroelectric power plant will produce the same amount of energy -
0.4PJ during the study period, due to luck of hydro potential in the country. Production of electricity by coal-fired power plant seems to be feasible for Moldova, and energy generated by coal is increasing from 3,5PJ in 2015 to 18.2PJ in 2030. Considering that Moldova is planning construction of 350MW of installed capacity by 2015, the MARKAL model shows that higher capacity is economically attractive to be constructed in the country. Figure 2.5 represents the Electricity Generation by Fuel [PJ]. (1 PJ = 277.7777778 GWh)
Construction of 130MW of coal-fired power plant is economically attractive starting with 2015. Construction of 170MW until 2018 and 100MW during 2018-2021 is feasible for the country. In the optimization process, MARKAL model chose 100MW in every following period. Figure 2.6 represents New Power Plants Builds by Fuel Type [GW]
Fig. 2.6. New Power Plants Builds by Fuel Type [GW]
Fig. 2.7. Lump Sum Investment in New Power Plants [2006MEuro]
Investment demand for least cost development of power generation sources is mainly driven by new coal-fired power plants. In year 2015 investment in coal power plant is 150 MEuro2006, and 170 MEuro until 2017. If the installed capacity of coal power plant will be extended, then 100 MEuro will be invested in every period from 2021. Figure 2.7 shows Lump Sum Investment in New Power Plants [2006MEuro] Natural Gas is only fuel used for power generation in Moldova in year 2006 and its consumption was 16PJ in base year, decreasing to 12 PJ in 2030. Coal power plant will use 8PJ of coal in 2015 and by 2018 becomes the main fuel for power generation with 19PJ of coal comparing to 14PJ of Natural gas. By 2030 coal becomes the main fuel for power generation and its amount is 44PJ. Figure 2.8 represents Fuel Consumption by Power Plants [PJ]
Fig. 2.8 Fuel Consumption by Power Plants [PJ]
3. Results
Total Discounted System Cost has the highest value for Reference Scenario (D_REF) - 11,206 MEuro for study period 2006 - 2030. The reason is that we assume that in this scenario no major changes of energy system will occur and the energy use will continue to have the same structure as today. As a result of Energy Efficiency (EE) scenario run (i.e.: scenario D_EE) the optimum solution decreased from 11,206 MEuro of Reference Scenario to 10,979 MEuro (Figure 3.1). We conclude that if all EE measures related to implementation of advances end-use devices will be implemented in the country, this will contribute to about 2% decreasing of system cost. And this 2 % decreasing of system cost represents the technical potential of energy saving at no cost, if we will need more energy saving measures, then the total discounted system cost will increase. Renewable Energy Scenario (D_RE) has a higher Total Discounted System Cost comparing to Energy Efficiency Scenario, due to high cost of renewable energy sources (in our case -wind energy is most attractive for the country) and lower cost comparing to Reference Scenario by
0.3%. However, implementation of Renewable Energy Sources together with Energy Efficiency measures seems to be cost effective (scenario D_EERE) and has a total discounted system cost lower by 1.9% comparing to Reference Scenario. The Renewable Scenario has a lower Total Discounted Cost comparing to Reference Scenario, this happens due to: earlier penetration of efficient demand devices than Reference , but higher cost of investment in renewable technologies is increasing the Total system cost.
Fig. 3.1. Total Discounted System Cost, MEuro
Implementation of Renewable Energy Sources (wind turbines of 1PJ/year by 2012 and 2 PJ/year by 2030) substitutes the demand of power generation by coal-fired power plants of about 2PJ per year starting with 2021 till 2030 (Figure 3.2). Energy efficiency measures decrease the demand of electricity generation by coal of up to 3PJ/year by 2030, due to more efficient end-use devices with lower electricity consumption. Combined implementation of Renewable Energy together with Energy Efficiency measure reduces the demand in new wind power plants to 1.5PJ/year by 2030 and substantial reduction of coal fired power plants production of up to 4,7PJ/year by 2030. Figure 3.2 represents the differences of Electricity Generation by Fuel Group + Imports (PJ) for Renewable, Energy Efficiency and Renewable and Energy Efficiency Scenarios comparing to Reference Scenario.
Comparing Reference Scenario with Renewable, Energy Efficiency and Renewable&Energy Efficiency Scenarios in terms of final energy by fuels we can conclude that: in Renewable Scenario the final energy consumption does not change, except a small replacement of electricity consumption by natural gas, mainly in 2015 (Figure 3.3); Energy Efficiency Scenario shows a substantial decreasing of demand of electricity of up to 3PJ/year by 2030 and reduction of gas consumption by 2PJ/year by 2030, due to more efficient end-use devices; Combined application of Renewable and Energy Efficiency Scenario has very similar final energy consumption with Energy Efficiency Scenario, except for more reduction in heat demand comparing to Reference Scenario.
Fig. 3.3. Energy Balance - Final Energy by Fuel, PJ
Interesting result from scenario analyses is that Renewable and Energy Efficiency Scenario has a substantial potential for reduction of electricity and natural gas consumption of up to 5PJ/year in 2030 comparing to Reference Scenario. The main sector with potential for final energy saving is Residential (minus 2 PJ/year by 2021 and minus 3.5PJ/year by 2030); followed by Industrial and Commercial sectors (minus 1 PJ/year by 2030 each) (Figure 3.4).
Final energy consumption by fuel was analyzed for: Agriculture, Commercial, Industry, Residential and Transport Sector. However, results only for Residential sector are presented in this paper (Figure 3.5). The reason is that Residential Sector has the major potential for energy savings (see Figure 3.4). For Residential Sector, in Renewable Scenario - Final energy consumption profile remains the same as in Reference Scenario except small trade-off between gas and electricity. Significant reductions in EE and EE&RE target scenarios is mainly due to the availability of more efficient end use devices using electricity and gas, of a total reduction capacity of up to 3.5PJ/year by 2030.
Fig. 3.5. Final Energy to RES by Fuel, PJ
Fig. 3.6. Energy Balance - Primary by Fuel Group, PJ
Primary energy consumption in Reference Scenario shows a decrease of coal consumption of up to 5PJ/year in 2021 and 6PJ/year in 2030 and more consumption of biomass comparing to
Reference Scenario of up to 2PJ/year in 2030 (Figure 3.6). Implementation of Energy Efficiency scenario decreases the coal demand by 4 PJ/year in 2021 and 6PJ/year in 2030; gas demand decreases to 2PJ/year by 2030. Renewable and Energy Efficiency Scenario has the highest potential of primary energy demand of up to 13 PJ by 2030: reduction of coal demand up to 8PJ/year by 2021 and 10PJ/year by 2030; reduction of natural gas demand of up to 2PJ/year by 2030 replaced by biomass demand increasing due to renewable energy potential implementation. If not considering investment cost, total annual expenditures on O&M and fuel for Scenarios analyzed are very similar between Renewable Scenario and Reference Scenario, except of about 100 MEuro reductions for 2012 due to wind power project and increasing expenditures up to 200MEuro in 2021 due to biomass utilization (Figure 3.7). Energy Efficiency Scenarios has substantial expenditures on fuel starting with 2012 due to implementation of advanced end-use technologies using gas that is replacing electricity. In long term this technologies are cost-effective and starting with 2024 over 100 MEuro/year are saved. Renewable and Energy Efficiency Scenario is very similar with Energy Efficiency Scenario, except small tradeoff in years 2012 and 2015.
600
500
400
300
200
100
0
-100
-200
-300
Difference from Refference, MEuro
1 ■ 1
1 I 1
1 ■
n
1 umm
0 2J2 2018 2024 2030 0 2012 2018 : 0 0 2012 2018 ;
"■1 ■1
Renewable Lnergy LTTICienCy KenewdDies aria tt
I Expenditure on Fuel
I Annualized Investment Cost
Fig. 3.7. Expenditures - Annual Inv + Fuel, MEuro
Renewable Energy Scenario has an investment demand of 120 MEuro in 2012 and in 2021 for construction of renewable power plants (wind and biomass) (Figure 3.8). Investment in renewable will reduce the demand of investment in coal-fired power plants by minus 44 MEuro in 2015 and minus 35MEuro in 2021. In case of renewable sources implementation it is necessary to invest in gas-turbine in 2018 - 11MEuro and 7MEuro by 2021. Energy Efficency Scenario has a reduction of up to minus 50 MEuro by 2021 in gas and coal-fired power plants due to reduction of electricity demand for advanced end-use energy equipment. Implementation of Renewables together with Energy Efficiency measures Scenario has the highest reduction of investment demand comparing to Reference Scenario. For year 2021 it is observed a reduction of up to 85 MEuro of demand in investment in coal and gas power plants. For the same year the demand of investment decreases for renewable to 70 MEuro.
Fig. 3.8. Lump Sum Inv in Power Plants, M Euros
Implementation of Renewable Scenario decreases gas demand for power generation plants by 3 PJ in 2015, and significant reduction of up to 6PJ/year in 2030 of coal for electricity generation. In the same time the demand of biomass is increasing of up to 4 PJ/year by 2030 (Figure 3.9). Energy Efficiency Scenario has a reduction of fuel demand for electricity generation of 1PJ/year in gas power plants and from 1PJ/yer in 2018 to 6PJ/year in 2010 for coal-fired power plants. Renewable energy together with Energy Efficiency measures applied in Renewables&EE Scenario have significant reduction of fuels for electricity generation of up to 10PJ/year in 2030 of coal, decreasing in the same time demand for biomass from 4PJ/year in 2030 in Renewable Scenario to 3PJ/year in 2030 for Renewable&EE Scenario.
Fig. 3.9. PP Consumption by Fuel Group, PJ
Renewable Scenario shows a demand of 120MW installed capacity of wind power plants already in 2012 and 110MWinstalled in 2021 (Figure 3.10). Also in this scenario it is necessary to build 25MW of gas-turbine by 2018 and 15MW by 2021, replacing 45MW of demand in construction of coal-fired power plants in 2015 and 30MW by 2021. Energy Efficiency Scenario has a reduction of demand in new coal-fired power plant of up to minus 35 MW installed/year in 2021, and up to minus 55MW installed/year by 2018 of gas power plant. Renewables&EE Scenario has a reduction to 50MW demand in renewable power plants comparing to Renewable Scenario in 2021 due to implementation of energy efficiency measures. In this Scenario it is observed high decreasing of coal power plant by 50 MW by year 2015 and 50 MW by 2021. After 2021 coal and gas power plants have a reduction in installed capacity of about 50MW/per year.
Fig. 3.10. New Power Plants Builds by Fuel Type, GW
Energy intensity is decreasing from 6.5 PJ/MEuro in 2006 to 3 PJ/MEuro in 2030 mainly due to replacement of existing inefficient energy technologies in all Scenarios.
4. Conclusions
1. Meeting renewable targets is cost-effective with application of advanced end-use technologies.
2. Key measures will be needed to shift investment from fossil to renewable generation
3. Encouraging uptake of more efficient technologies is a priority issue as the economic potential for energy saving is significant
4. Combining EE and RET scenarios leads to more efficient energy system
5. Residential sector is most interesting for implementation of energy efficiency measures.
6. MARKAL database at least for 2006 to be published on the web www.kanors.com/DCM/RES2020
References
1. Richard Loulou, Gary Goldstein, Ken Noble “Documentation for the MARKAL Family of Models”, Energy Technology Systems Analysis Programme, http://www.etsap.org
2. Wolfgang Eichhammer, Rainer Walz “Indicators to measure the contribution of Energy Efficiency and Renewables to the Lisbon targets. Monitoring of Energy Efficiency in EU 27, Norway and Croatia (ODYSSEE-MURE)”, Fraunhofer Institute for Systems and Innovation Research (Fraunhofer ISI) 2009
3. “World Energy Outlook 2010”, International Energy Agency
4. National Bureau of Statistics of the Republic of Moldova, http://www.statistica.md
5. National Agency for Energy Regulation, http://www.anre.md
6. UNDP Moldova, http://www.undp.md
7. Bozic, H., "Optimization of Energy Consumption and Energy Efficiency Measures with MARKAL Model”, http://ieeexplore.ieee.org/xpl/freeabs all.jsp?arnumber=4272397
8. IISD Canada “MARKAL-EQUITY program”, http://www.iisd.org/energy/markal.asp
9. IRG “First US MARKAL/TIMES Symposium”,
http://www.irgltd.com/Our Work/Services/First%20US%20MARKAL-TIMES%20Symposium.html
10. J.R. Ybema, T. Kram, “Markal Modelling And Scenarios Relating To Availability Of New Energy Technologies”, http://www.ecn.nl/docs/library/report/1997/rx97072.pdf
11. Mohammad Reza Faraji Zonooz, “A Review of MARKAL Energy Modeling”, http://www.eurojournals.com/ejsr 26 3 03.pdf
12. Levin, T.J. Thomas, V.M. Lee, A.J. “A MARKAL model of state electricity generation”, http://ieeexplore.ieee.org/Xplore/login.jsp?url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2 F5496818%2F5507674%2F05507755.pdf%3Farnumber%3D5507755&authDecision=-203
13. Ingrid Nystrom and Clas-Otto Wene, “Energy-economy linking in MARKAL-MACRO: interplay of nuclear, conservation and CO2 policies in Sweden”,
http://inderscience.metapress.com/app/home/contribution.asp?referrer=parent&backto=issue,12,1 3;j ournal,85,93;linkingpublicationresults,1:110851,1
14. Amit Kanudia, Maryse Labriet, Richard Loulou, Kathleen Vaillancourt and Jean-Philippe Waaub,” The World-Markal Model and Its Application to Cost-Effectiveness, Permit Sharing, and Cost-Benefit Analyses”, http://www.springerlink.com/content/jq37822035j08668/
About authors
Sergiu Robu - scientific researcher of the Laboratory of Energy Efficiency and Control Systems of the Institute of Power Engineering of the ASM (www.ie.asm.md ). Research interests are: long term planning of energy systems; energy efficiency; models and methods for the development of Energy Systems; management and economy of Energy Systems; scenarios/environmental wastes from energy chains. National Expert in long term planning using ENPEP, MARKAL, WASP-Win., SIMPACTS, MESSAGE, GAINS and other computer models. e-mail: [email protected]
Dr. George Giannakidis, CRES - Centre for Renewable Energy Sources, Greece (www.cres.gr). Research interests are energy policy and models for renewable sources development, MARKAL Model application in developing countries, long term energy planning: e-mail: [email protected]
Philip Siakkis, CRES - Centre for Renewable Energy Sources, Greece (www.cres.gr). Research interests are application of advanced models for energy policy analyses, MARKAL application for regional studies, energy efficiency and economics, scenarios of regional energy systems: e-mail: [email protected]
Elena Bykova - scientific researcher of the Laboratory of Controlled Transmission Lines of the Institute of Power Engineering of the ASM (www.ie.asm.md ). Professional interests are: systems analysis in the energy sector, development of energy systems, process modeling in the energy sector, the methodology of calculating and monitoring indicators for the energy security of the country (region), modern technologies of production of electricity and heat, new transmission and distribution of electric energy, monitoring GHG-emissions, studies of energy balance and the perspective development of energy sector. National Expert on greenhouse gas emissions, Markal system. Participated in several international projects Fichner, Energy Security, Development of energy systems, etc. e-mail: [email protected].
